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dc.contributor.advisorCharlton, William S.
dc.creatorFord, David Grant
dc.date.accessioned2010-01-15T00:10:47Z
dc.date.accessioned2010-01-16T00:56:44Z
dc.date.available2010-01-15T00:10:47Z
dc.date.available2010-01-16T00:56:44Z
dc.date.created2008-05
dc.date.issued2009-05-15
dc.identifier.urihttps://hdl.handle.net/1969.1/ETD-TAMU-2786
dc.description.abstractAn assessment methodology has been developed at Texas A&M University for predicting weapons useable material acquisition by a terrorist organization or rogue state based on an acquisition network simulation. The network has been designed to include all of the materials, facilities, and expertise (each of which are represented by a unique node) that must be obtained to acquire Special Nuclear Material (SNM). Using various historical cases and open source expert opinion, the resources required to successfully obtain the goal of every node within the network was determined. A visual representation of the network was created within Microsoft Visio and uses Visual Basic for Applications (VBA) to analyze the network. This tool can be used to predict the most likely pathway(s) that a predefined organization would take in attempting to acquire SNM. The methodology uses the resources available to the organization, along with any of the nodes to which the organization may already have access, to determine which path the organization is most likely to attempt. Using this resource based decision model, various sample simulations were run to exercise the program. The results of these simulations were in accordance with what was expected for the resources allocated to the organization being modeled. The program was demonstrated to show that it was capable of taking many complex resources considerations into account and modeled them accurately.en
dc.format.mediumelectronicen
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.subjectnuclear terrorismen
dc.subjectresource based decision theoryen
dc.titleAssessment tool for nuclear material acquisition pathwaysen
dc.typeBooken
dc.typeThesisen
thesis.degree.departmentNuclear Engineeringen
thesis.degree.disciplineNuclear Engineeringen
thesis.degree.grantorTexas A&M Universityen
thesis.degree.nameMaster of Scienceen
thesis.degree.levelMastersen
dc.contributor.committeeMemberMcIntyre, David H.
dc.contributor.committeeMemberNelson, Paul
dc.type.genreElectronic Thesisen
dc.type.materialtexten
dc.format.digitalOriginborn digitalen


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